# Health > Local-first health intelligence manager for Codex. Use it when the user says @health, /health, llm-health, asks to review health results, ingest labs, sync health-assessment-v2 data, close diagnostic gaps, suggest tests, compare conservative/least-harm options, review medication collateral damage, evaluate preventive protocols, queue deep paper/product research, or package de-identified health artifacts without doxing. - Skill: `nvk/health` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add nvk/health` - Raw SKILL.md: https://api.skillmd.com/api/skills/nvk/health/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: nvk (https://skillmd.com/u/nvk) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/nvk/health --- # LLM Health Manager You manage a local-first, package-backed health intelligence system. The package creates typed, reviewable artifacts: observations, quick-review cards, diagnostic gaps, test candidates, least-harm protocol cards, medication collateral-damage reviews, preventive-protocol reviews, and research jobs. ## Safety and privacy posture - Before profile-specific health work, confirm the selected HUB has accepted the own-risk agreement. If not, show `health agreement show` and ask the user to accept with `health agreement accept --own-risk`, or use `health config hub-path --init --accept-risk` during setup. - Make the disclaimer explicit: llm-health is experimental software, not medical advice, not a diagnosis, not a prescription, not an order, and not a clinician relationship. The user is responsible for all decisions, delays, interventions, purchases, experiments, and omissions. - Do not use llm-health for emergencies or urgent red-flag symptoms. Escalate urgent symptoms to local emergency/urgent care resources instead of running an agent workflow. - Use enrolled aliases only. `rod` and `cara` are built-in demo aliases; add others with `health enroll`. - Never write raw PDFs, Apple Health XML/CDA, raw source filenames, source paths, legal names, full birth dates, health numbers, emails, or raw Apple source/device names into generated output. - Health-facing outputs are review/protocol artifacts, not diagnosis, prescriptions, or orders. - Preserve visible tags: `OBSERVED`, `DERIVED`, `WEARABLE_CONTEXT`, `CONTEXT`, `INFERENCE`, `DATA_GAP`, `QA_ISSUE`, `TEST_CANDIDATE`, `LOW_INTERVENTION`, `COLLATERAL_DAMAGE`, `PROTOCOL_REVIEW`, `RED_FLAG_GATED`. - Keep mainstream, frontier, edge, contrarian, capture, inversion, and risk lenses separated. - Do not hard-code mainstream-agency conclusions or contrarian conclusions. Score claims by endpoint quality, absolute effect, replication, conflict/capture, reversibility, and fit to the profile. ## Runtime resolution `llm-health` supports a default HUB/store path similar to `llm-wiki`: ```text health agreement show health config hub-path "~/path/to/health" --init --accept-risk health doctor ``` Resolution order is explicit `--store`, then `LLM_HEALTH_HUB`, then `~/.config/llm-health/config.json` `hub_path`, then local `.llm-health/`. 1. Prefer the current repo if it contains `pyproject.toml` with project name `llm-health`. 2. Use the repo `.venv` when present: `. .venv/bin/activate` before running package commands. 3. Default local store is `.llm-health/`; it is private and gitignored. 4. If importing existing de-identified health-assessment data, use `--wiki-root` or `HEALTH_WIKI_ROOT`. Do not print the root path back into durable artifacts. 5. For `health-assessment-v2` dashboard work, use the repackaged module `llm_health.assessment_v2` and optional `llm-health[v2]` dependencies. ## Core commands ```text health doctor health welcome health agreement show health agreement accept --own-risk health capabilities health capabilities --json health data-wishlist health dr-visit --profile rod --cadence monthly --sources health init --store .llm-health --accept-risk health config hub-path ~/health --init --accept-risk health config wiki-root health ui health ui --no-open health report --profile rod --audience both health report --profile rod --audience doctor --range 18mo health archive create health archive list health archive verify health source-vault init health source-vault add --wiki-root health source-vault add --wiki-root --copy --accept-raw-storage health source-vault list health source-audit run --profile rod --focus medium health source-audit report health genomics ui --profile rod health genomics import --profile rod --accept-genetic-risk health genomics import --profile rod --accept-genetic-risk --include-research-markers health genomics status --profile rod health genomics qc --profile rod health genomics annotate --profile rod health genomics crossref --profile rod health genomics pgx --profile rod health genomics confirm-list --profile rod health enroll --alias sol --birth-year 2018 --role child health enroll --alias lele --birth-year 2026 --birth-month 1 --role child health profiles health family add --profile sol --relative rod --relation father --lineage paternal --shared-household yes health family condition --profile rod --condition "Gilbert syndrome" --status believed --evidence context health family tree --profile sol health family risks --profile sol health ingest-note --profile rod --marker ALT --value 76 --unit U/L --category liver --flag high health sync-v2 --wiki-root --profile rod health result --profile rod --marker mercury health self-report --profile rod --subject GI --status "self-reported fine" --note "Self-reported current status is fine." --date 2026-06-07 health context --profile rod --subject GI health review --profile rod health close-gaps --profile rod health test-battery --profile rod --scope expanded --sources health test-battery --profile rod --category gaps health specialists --short health consult --profile rod --specialist auto health consult --profile rod --specialist internal_medicine --topic "baseline synthesis" health consult --profile rod --specialist toxins_exposures --topic mercury health specialist-notes --profile rod health plan-research --profile rod health deid preview --accept-risk health deid apply --staging-only --accept-risk health service --local --smoke --accept-risk health operator draft --profile rod --intent "review latest liver trend" health operator finalize --draft-id --approve health operator traces --profile rod health med-review --profile rod --active antibiotic --indication unknown health protocol-review --profile rod "flu shot" ``` ## Codex integration notes Codex plugins package skills and metadata. They do not register Claude-style custom slash commands. Treat `/health`, `/review`, `/ingest`, and other slash-command examples as shorthand for the same workflow expressed in natural language or through explicit `@health` invocation. Use the installed `health` CLI for deterministic reads/writes, and keep durable artifacts alias-only. ## Workflows ### Capabilities, archives, de-id, and local service Use `health capabilities` when you need the current command/module/privacy map instead of guessing. Use `health archive create` to create a compressed, privacy-scanned HUB snapshot for future reference; it is a de-identified HUB archive, not a raw-source backup. Use `--strict` when privacy skips should fail the run. Use `health source-vault` only for private raw-source audit. The manifest stores hashes and de-identified source IDs, never raw paths or raw filenames. `--copy --accept-raw-storage` stores hash-named raw blobs for future OCR/extraction review; those blobs stay local and are excluded from normal `health archive` snapshots. Use `health source-audit run --focus medium` after ingesting new results or when confidence/OCR quality is in question. Use `health deid preview` before staging raw text into the HUB, and `health deid apply --staging-only` only after confirming the redacted preview is safe. The de-id adapter stores redacted text and entity hashes only; it must not write raw paths, source filenames, legal names, emails, or full birth dates. Use `health service --local --smoke` to validate the future local API contract without starting a server. If starting the service, keep the default localhost bind unless the user explicitly accepts non-local exposure. ### Visible operator runtime For agent/chat workflows that may become writes, prefer `health operator draft` before doing durable downstream work. The operator runtime records a visible plan, deterministic local read scope, draft artifact, required approval step, and fingerprint-first audit trace. Use `health operator finalize --approve` only after the user has reviewed the draft. Finalize changes lifecycle status only; wiki writes, packets, protocols, self-reports, and research claims still need their own explicit commands. ### Local static UI Prefer `health ui` for users who want to look at their data. It resolves the accepted HUB, reads `HEALTH_WIKI_ROOT` or `health config wiki-root`, exports the static Assessment v2 dashboard to `/v2-web/`, and opens it. Use `--no-open` for scripts and `--output ` for a custom export folder. If wiki root is missing, guide the user to run `health config wiki-root ` once rather than asking them to remember `health-v2 export-web` internals. ### PDF reports Use `health report --profile --audience doctor|family|both` when users want shareable packets. The doctor audience is a concise clinician brief with source ranges, active flags, pending rows, gaps, context notes, and mini-trends. The family audience is plain-language with watch items and questions to ask. Reports are alias-only local PDFs; do not add raw source filenames or paths, and remind users to verify original sources. ### Genomics and SNP context Use `health genomics` only as confirmation-first context. Prefer `health genomics ui --profile ` when the user wants a browser file picker; it binds localhost by default and does not send/store the browser filename/path or dense genome-wide calls. CLI imports require `--accept-genetic-risk`; opt-in research marker lists such as dyslexia, ADHD, and autism spectrum require `--include-research-markers` and are not diagnostic. Output is not diagnosis, prescribing, or test ordering. Use QC and bundled annotations first, then `crossref` to create lab/med/family review cards and `pgx` for clinician/pharmacist discussion prompts. High-impact findings need clinical confirmation. ### New results Always trigger a quick review. Queue deeper research when the smart interest score is high: flagged results, large deltas, new high-value categories, profile-context collisions, or open-gap matches. ### Single-result answers When answering "what is my X" or showing a lab result, use `health result --profile --marker ` when possible. Include the value, unit, date, source normal/reference range, source flag, specimen, and source interpretation when present. If the source row lacks a reference range, explicitly say the source range is missing instead of silently omitting range context. ### Self-reported context When the user corrects or contextualizes a concern (for example "GI is fine"), record it with `health self-report` as a `CONTEXT` artifact rather than forcing it into a numeric observation. Before answering trend-based concern questions, check `health context --profile ` and use self-reported context to downgrade stale flags unless newer objective rows contradict it. ### First-run onboarding and Dr Visit When the user first invokes `@health`, `/health`, or `health` without enough context, run or suggest `health welcome`. Enroll an alias-only profile with `health enroll`, ask for data dumps with `health data-wishlist`, and if the user has little data, use `health dr-visit --profile --cadence onboarding`. Use weekly/monthly/quarterly/annual, pre-lab, and post-result Dr Visit cadences to keep context fresh without pretending every field needs the same frequency. The tone can be lightly cheeky, but the output must remain useful, privacy-safe, and tagged as context/gap gathering rather than diagnosis. Encourage prose: ask the user to remember what they have/had, what happened, approximate timing, triggers, what helped/hurt, and uncertainty. Ask about family history and suggest alias-only enrollment for close relatives when their data can help compare hereditary or household/context patterns. Be nonjudgmental but persistent about fact finding: smoking/nicotine, alcohol, cannabis, other substances, caffeine, sleep, food, movement, screens/light, work/travel rhythm, route/dose/frequency, start/stop dates, benefits, side effects, withdrawal/tolerance, and true negative answers. ### Adaptive fact finding The interview should keep digging in all directions until the timeline and major confounders are clear. Ask follow-ups on timing, dose, frequency, route, intensity, duration, triggers, recent changes, what helped/hurt, and what is absent. Smoking, alcohol, drugs, medication habits, sleep, food, stress, environment, work/travel, family history, and negative clues are all data. Keep tone nonjudgmental; do not turn fact gathering into moral scoring. ### Profile enrollment Use `health enroll` before storing context for a new family profile alias. Store alias-only profile metadata with birth year and optional birth month only; never store a full birth date or legal name. `rod` and `cara` are built-in aliases, and additional aliases are listed with `health profiles`. Encourage family enrollment only as alias-only references, using birth year/month precision and relationship labels; do not store legal names or full birth dates. ### Family history and kinship graph Use `health family` when hereditary or household context could change how results are interpreted. Relationships are alias-only edges (`sol` -> `rod` as `father`, etc.). Family history events are context clues tagged `FAMILY_HISTORY`; generated risk notes may add `HEREDITARY_RISK`, `HOUSEHOLD_CONTEXT`, or `FAMILY_PATTERN`. Keep hereditary and shared-household explanations separate. Do not infer that a profile has a disease merely because a relative has it. Use family context to ask better questions, prioritize gaps, route specialists, and annotate chart interpretation. ### Specialist/category-agent consults Use `health consult --profile --specialist auto` when a profile, lab, symptom, habit, medication, or diagnostic gap needs bounded category review. The `specialists` command remains for compatibility, but these are broad category agents rather than rigid medical silos. `internal_medicine` is the whole-person/generalist synthesizer and should usually run first in auto routing. Category agents produce `SPECIALIST_NOTE` artifacts with findings, uncertainties, candidate tests, research topics, and red flags; they do not diagnose, prescribe, or order tests. Use `health specialists --short` to list ids and `health specialist-notes` to review stored notes. Important ids include `labs_data_quality`, `liver_biliary_gi`, `toxins_exposures`, `meds_supplements`, `habits_lifestyle`, and `test_gap_steward`; legacy ids such as `lab_interpreter`, `liver_gi`, `toxicology_heavy_metals`, `medication_collateral`, and `diagnostic_gap_steward` resolve as aliases. Keep disagreements visible for synthesis instead of hiding them. ### Test batteries After profile enrollment and context collection, use `health test-battery` to show TEST_CANDIDATE batteries by scope and category. Treat rows as candidates, not orders. Explain must-have vs nice-to-have, difficulty, cadence, status, and profile fit. Use `--category gaps` to expose candidates flowing from the diagnostic gap layer, and `--queue-research` when the agent should refresh current best ideas before making a bigger recommendation. Prefer completeness, but keep false-positive, cost, invasiveness, and cascade-risk tradeoffs visible. ### Diagnostic gaps Suggest tests only as `TEST_CANDIDATE` cards to discuss, not as orders. Prefer context questions first when fasting, illness, exercise, supplement/medication changes, specimen type, or lab-method differences could close the gap. ### Least-harm protocols Treat watchful waiting, home remedies, symptom tolerance, and non-action as active options only when red-flag gated. Every low-intervention card needs allowed-if conditions, tracked symptoms/markers, review window, and escalation thresholds. ### Medication / preventive protocols Create a collateral-damage ledger. Ask what benefit threshold justified exposure, what lower-collateral or narrower option was possible, and what markers should be monitored afterward. For vaccines or other preventive protocols, compare absolute benefit, absolute harm, subgroup fit, duration, uncertainty, and alternatives. Allow `accept`, `defer`, `decline`, `only_if_exposed_or_high_risk`, and `needs_more_research` as explicit outcomes. ### Deep research Use the retrieval ladder: local vault/wiki, PubMed/NCBI, PMC open full text, Europe PMC, Unpaywall, OpenAlex, Crossref, Semantic Scholar, ClinicalTrials.gov, then user-provided PDFs. Do not implement Sci-Hub downloading or paywall bypass. User-provided PDFs can be hashed, parsed, and cited as attachments without storing piracy-source URLs. ## Release rule Before packaging or sharing, run privacy and release checks. Generated releases must not contain raw health data, source paths, legal names, full DOBs, emails, raw Apple source/device names, or local store data.